In this vein, recent work [1]}, [2]} in music information retrieval has demonstrated that Jukebox [3]}, a large GPT-style model trained on 1M songs to generate raw music audio, contains representations that serve as strong features for music audio prediction tasks.
We take inspiration from these advances and extract Jukebox features as the conditioning input for our diffusion model, and develop a new memory-efficient implementation that enables near real-time extraction on a single commodity GPU (see sec:appendixjukemem for details).
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